tlo.methods.simplified_births module
This is the SimplifiedBirths Module. It aims causes pregnancy, deliveries and births to occur to match WPP estimates of total births. It subsumes the functions of several other modules (contraception, labour, pregnant supervisor, postnatal supervisor, newborn outcomes) , allowing for faster runnning when these are not required. The main assumption is that every pregnancy results in a birth.
- class SimplifiedBirths(name=None, resourcefilepath=None)
A simplified births module responsible for generating births in a simplified way and assign mother ids to newborns.
Construct a new disease module ready to be included in a simulation.
Initialises an empty parameters dictionary and module-specific random number generator.
- Parameters:
name – the name to use for this module. Defaults to the concrete subclass’ name.
Bases:
tlo.core.Module
PARAMETERS:
Item
Type
Description
age_specific_fertility_rates
DATA_FRAME
Data table from official source (WPP) for age-specific fertility rates and calendar period
months_between_pregnancy_and_delivery
INT
number of whole months that elapase betweeen pregnancy and delivery
prob_breastfeeding_type
LIST
probabilities that a woman is: 1) not breastfeeding (none); 2) non-exclusively breastfeeding (non_exclusive); 3)exclusively breastfeeding at birth (until 6 months) (exclusive)
PROPERTIES:
Item
Type
Description
si_date_of_last_delivery
DATE
Date of delivery for the most recent pregnancy for this individual (if has ever been pregnant). Maybe in the future if is currently pregnant.
si_breastfeeding_status_6mo_to_23mo
CATEGORICAL
How this neonate is breastfeed during ages 6mo to 23 months. Possible values are: [none, non_exclusive, exclusive, ]
is_pregnant
BOOL
Whether this individual is currently pregnant
date_of_last_pregnancy
DATE
Date of the onset of the last pregnancy of this individual (if has ever been pregnant).
nb_low_birth_weight_status
CATEGORICAL
temporary property. Possible values are: [extremely_low_birth_weight, very_low_birth_weight, low_birth_weight, normal_birth_weight, macrosomia, ]
nb_size_for_gestational_age
CATEGORICAL
temporary property. Possible values are: [small_for_gestational_age, average_for_gestational_age, large_for_gestational_age, ]
nb_late_preterm
BOOL
temporary property
nb_early_preterm
BOOL
temporary property
nb_breastfeeding_status
CATEGORICAL
temporary property. Possible values are: [none, non_exclusive, exclusive, ]
Class attributes:
ALTERNATIVE_TO : {‘NewbornOutcomes’, ‘Contraception’, ‘Labour’, ‘PostnatalSupervisor’, ‘PregnancySupervisor’}
INIT_DEPENDENCIES : {‘Demography’}
METADATA : {}
__annotations__ : {}
Functions (defined or overridden in class SimplifiedBirths):
- __init__(name=None, resourcefilepath=None)
Construct a new disease module ready to be included in a simulation.
Initialises an empty parameters dictionary and module-specific random number generator.
- Parameters:
name – the name to use for this module. Defaults to the concrete subclass’ name.
- read_parameters(data_folder)
Load parameters for probability of pregnancy/birth and breastfeeding status for newborns
- initialise_population(population)
Set property values to their defaults for the initial population.
- initialise_simulation(sim)
Schedule the SimplifiedBirthsPoll and the SimplifiedBirthEvent to occur every month.
- on_birth(mother_id, child_id)
Initialise properties for a newborn individual to their defaults.
- class SimplifiedBirthsPoll(module)
Create a new regular event.
- Parameters:
module – the module that created this event
frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)
Bases:
tlo.events.RegularEvent
,tlo.events.Event
,tlo.events.PopulationScopeEventMixin
Class attributes:
__annotations__ : {}
Functions (defined or overridden in class SimplifiedBirthsPoll):
- __init__(module)
Create a new regular event.
- Parameters:
module – the module that created this event
frequency (pandas.tseries.offsets.DateOffset) – the interval from one occurrence to the next (must be supplied as a keyword argument)
- apply(population)
Apply this event to the given target.
This is a no-op; subclasses should override this method.
- Parameters:
target – the target of the event
- set_new_pregnancies()
Making women pregnant. Rate of doing so is based on age-specific fertility rates under assumption that every pregnancy results in a birth.
- do_deliveries()
Checks to see if the date-of-delivery for pregnant women has been reached and implement births where appropriate.
- update_breastfed_status()
Update the bread_fed status of newborns, mirroing the functionality provided by the Newborn module